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Bioconcentration factors for hydrocarbons and petrochemicals: Understanding processes, uncertainty and predictive
L Camenzuli1, C W Davis2, T F Parkerton3
1ExxonMobil Petroleum & Chemical, Machelen, Belgium.
Chemosphere
|April 6, 2019
Summary
This study generated fish bioconcentration factor (BCF) data for 21 substances using rainbow trout. It found that structural features influence BCFs and current uncertainty estimations are inadequate.
Area of Science:
- Environmental Toxicology
- Ecotoxicology
- Chemical Risk Assessment
Background:
- Fish bioconcentration factors (BCFs) are crucial for assessing bioaccumulation, but reliable data are scarce due to experimental challenges.
- Understanding factors influencing BCFs is vital for accurate environmental risk assessment and regulatory decision-making.
Purpose of the Study:
- To generate empirical BCF data for 21 substances using rainbow trout with tailored experimental designs.
- To investigate the relationship between chemical structure and BCF magnitude and uncertainty.
- To evaluate the performance of six quantitative structure-property relationships (QSPRs) for predicting bioaccumulation.
Main Methods:
- Conducted nine laboratory studies using rainbow trout to determine steady-state BCFs for 21 diverse test substances.
- Analyzed BCF data in relation to chemical structure, uptake clearance, elimination rates, and biotransformation.
- Assessed six QSPRs against measured BCFs and evaluated uncertainty quantification methods.
Main Results:
- Measured BCFs ranged from 12 Lkg-1 (isodecanol) to 15,448 Lkg-1 (hexachlorobenzene), adjusted for 5% lipid content.
- Hydrocarbon BCFs were linked to aromatic/saturated ring configurations and substituent positions.
- Gill metabolism, bioavailability, and somatic biotransformation influenced uptake and elimination rates.
- Current uncertainty estimates for experimental BCFs significantly underestimate true variability.
- The Vega (KNN/Read-Across) QSPR and Arnot-Gobas model demonstrated the best predictive performance.
Conclusions:
- Empirical BCF data and structure-activity relationships provide insights into bioaccumulation potential.
- Existing methods for quantifying uncertainty in experimental BCFs require revision for improved risk assessment.
- The Vega and Arnot-Gobas models show promise for predicting fish bioaccumulation, aiding regulatory assessments.
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